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In the second dataset, coherence changes discretely reflecting a jump from one frequency to another over time.
Fig. 1 Flowchart illustrating the current uses of SAR imagery and InSAR timeseries observations for volcano monitoring through the use of amplitude images, coherence changes in phase, ground displacements from differential InSAR and topographic change detection.
Second, each of these conditions caused a distinct pattern of coherence changes between the same regions of the network.
A quantitative analysis of all coherence changes within the network in both ranges showed that this tendency generally holds for all pairs of brain regions.
We conclude that the distinct arousal states are characterized by distinct patterns of coherence changes within that same network of brain regions.
These sustained coherence changes have been shown to follow a retinotopic organization in V1 but are largely absent in the prestriate cortex (V2) (Rols et al., 2001).
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In the first dataset coherence changed continuously over time.
They demonstrated that the coherence change reflected the degree of urban damage.
Table 2. SAR datasets used to estimate general trends of temporal coherence change before earthquake.
Then, according to Eq. (6), we calculated the coherence change threshold at each pixel.
Therefore, we estimated the coherence change threshold at each pixel using the average and standard deviation of the coherence change caused by other temporal effects, which appears in the coherence difference maps.
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